Common errors in statistics (and how to avoid them)

The previous editions have proven to be successful guides for choosing and using the right techniques. Common Errors is consistently coherent and provides a consistent level throughout. The Third Edition elaborates on many key topicssuch as response variables, errors in testing hypothesis, higher order experimental design, curve fitting and magic beans, Poisson and negative binomial regression, correcting for confounding variables, dynamic models, factor analysis, general linear models, decision trees, etc. One new chapter has been added on ‘Statistical Analysis’ and includes sections on data quality assessment, data review, and design review. Modifications have been included throughout the book, and many new figures have also been added. Topics covered include creating a research plan, collecting data, formulating and testing a hypothesis, estimating coefficients, specifying sample size, checking assumptions, interpreting p-values and confidence intervals, building a model, reporting results, data mining, Bayes' Theorem, the bootstrap, and many others.

• ISBN: 978-0-470-45798-6
• Editorial: John Wiley & Sons
• Encuadernacion: Rústica
• Páginas: 273
• Fecha Publicación: 08/07/2009
• Nº Volúmenes: 1
• Idioma: Inglés